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--- |
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license: apache-2.0 |
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base_model: monologg/koelectra-base-v3-discriminator |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: koelectra-base-v3-discriminator-KEmoFact-0925 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# koelectra-base-v3-discriminator-KEmoFact-0925 |
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This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0290 |
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- Precision: 0.1739 |
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- Recall: 0.2415 |
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- F1: 0.2022 |
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- Accuracy: 0.7191 |
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- Jaccard Scores: 0.6892 |
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- Cls Accuracy: 0.6197 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Jaccard Scores | Cls Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:--------------:|:------------:| |
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| No log | 1.0 | 414 | 1.1425 | 0.0698 | 0.0726 | 0.0711 | 0.7029 | 0.4752 | 0.4204 | |
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| 1.4439 | 2.0 | 828 | 1.0332 | 0.1119 | 0.1676 | 0.1342 | 0.7112 | 0.6452 | 0.5753 | |
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| 0.9159 | 3.0 | 1242 | 0.9799 | 0.1438 | 0.1912 | 0.1642 | 0.7302 | 0.6322 | 0.5977 | |
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| 0.6814 | 4.0 | 1656 | 1.0124 | 0.1512 | 0.2064 | 0.1745 | 0.7265 | 0.6575 | 0.6189 | |
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| 0.538 | 5.0 | 2070 | 1.0331 | 0.1582 | 0.2199 | 0.1840 | 0.7205 | 0.6682 | 0.6195 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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